Intuit Staff Fraud Risk Analyst 

United States, California, Mountain View 

975028376

• Apply advanced analytics techniques and predictive modeling to develop actionable business insights.
• Build and enhance data, self-service, and analytics capabilities to streamline processes, drive decision-making, and empower stakeholders with meaningful insights.
• Analyze the holistic customer experience throughout their lifecycle, identifying opportunities to improve customer outcomes and deliver business value.
• Utilize operations research and statistical methodologies to optimize operational strategies, enhance customer experiences, and evaluate ROI.
• Provide strategic recommendations based on multiple data sources, business knowledge, and assumptions, even in cases of incomplete information.
• Identify business opportunities, influence key stakeholders, and drive action.
• Optimize data collection and processing to deliver clear visibility into the impact and value of initiatives and product launches.

Bay Area California $172,000 - $232,500

This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at

• Strong business acumen and exceptional analytical ability with 6+ years of industry experience with data analysis/data science/operation research.
• 5+ years of experience in modern advanced analytical tools and programming languages such as R or Python with pandas, matplotlib, and scikit-learn etc.
• Efficient in SQL, Hive and analytical BI tools such as Tableau, Quicksight etc.
• Hands-on expertise with data mining and statistical modeling techniques such as clustering, classification, regression etc.
• Proven track record of influencing cross-functional team decisions through data-driven recommendations.
• Excellent written and verbal communication skills, with the ability to synthesize complex data into clear narratives.
• Demonstrated ability to lead cross-functional initiatives and align stakeholders across many teams through analytics.
• BS, MS or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent
• Experience with AWS is plus